The growing application of Artificial Intelligence (AI) is transforming manufacturing industries across the globe by improving productivity and operational efficiency. However, in developing economies such as Zimbabwe, the extent to which AI adoption contributes to profitability remains inadequately explored. This study examines the impact of AI adoption on profitability in Zimbabwe’s manufacturing sector using a systematic review of secondary data from sources published between 2000 and 2026. The analysis is anchored in the Technology Acceptance Model (Venkatesh and Bala, 2008), the Resource-Based View (Barney, 1991), and Schumpeter’s Innovation Theory (Schumpeter, 1934). The findings suggest that AI adoption enhances firm performance by streamlining production processes, lowering operational costs, and enabling data-driven decision-making (Brynjolfsson and McAfee, 2014; McKinsey Global Institute, 2018). However, adoption remains constrained by high implementation costs, inadequate infrastructure, limited technical expertise, and regulatory uncertainty (Acemoglu and Restrepo, 2018; Ndung’u and Signé, 2020). The study recommends investment in digital infrastructure, skills development, and policy frameworks to facilitate AI integration. These insights are valuable for policymakers and industry stakeholders seeking to improve competitiveness and profitability in Zimbabwe’s manufacturing sector.